ERIC Number: EJ1476884
Record Type: Journal
Publication Date: 2025-Sep
Pages: 29
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0735-6331
EISSN: EISSN-1541-4140
Available Date: 0000-00-00
A Generative Artificial Intelligence (AI)-Based Human-Computer Collaborative Programming Learning Method to Improve Computational Thinking, Learning Attitudes, and Learning Achievement
Gang Zhao1; Lijun Yang1; Biling Hu2; Jing Wang1
Journal of Educational Computing Research, v63 n5 p1059-1087 2025
Human-computer collaboration is an effective way to learn programming courses. However, most existing human-computer collaborative programming learning is supported by traditional computers with a relatively low level of personalized interaction, which greatly limits the efficiency of students' efficiency of programming learning and development of computational thinking. To address the above issues, this study introduces generative AI into human-computer collaborative programming learning and proposes a dialogue-negotiated human-computer collaborative programming learning method based on generative AI. The method focuses on the problems-solving process and constructs multiple agents through Prompt design, which enable students to improve their computational thinking and master programming skills in the process of human-computer interaction for problem-solving. Finally, a quasi-experiment was conducted to verify the effectiveness of the proposed method in a 10th grade computer programming course in a high school. 43 students in the experimental group learned with the proposed method, while 42 students in the control group adopted the traditional computer-supported human-computer collaborative programming learning method. The experimental results showed that the proposed method more significantly improved students' computational thinking, programming learning attitudes, and learning achievement. This study provides theoretical foundations and application reference for future generative AI-assisted human-computer collaborative teaching.
Descriptors: Artificial Intelligence, Man Machine Systems, Programming, Learning Strategies, Computation, Thinking Skills, Skill Development, Student Attitudes, Academic Achievement, Cooperative Learning, Interaction, Prompting, Problem Solving, High School Students, Grade 10, Foreign Countries
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Publication Type: Journal Articles; Reports - Research
Education Level: High Schools; Secondary Education; Grade 10
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China
Grant or Contract Numbers: N/A
Author Affiliations: 1Hubei Key Laboratory of Digital Education, Faculty of Artficial Intelligence in Education, Central China Normal University, Wuhan City, China; 2Shenzhen Experimental School, Guangdong City, China